1. Field of the Invention
The present invention relates to a pattern recognition apparatus using a parallel operation.
2. Description of the Related Art
Image/speech recognition techniques can be generally classified into two types. In one type, a recognition algorithm specialized for recognition of a particular type of image/voice is described in the form of computer software and executed sequentially. In the other type, recognition is performed using a dedicated parallel image processor (such as a SIMD or MIMD machine).
One widely-used image recognition algorithm is to calculate a feature value indicating the degree of similarity between an image of an object and an object model. In this technique, model data of an object to be recognized is represented in the form of a template model, and recognition is performed by calculating the degree of similarity between an input image (or a feature vector thereof) and a template or by calculating a high-order correlation coefficient. The calculation may be performed by means of hierarchical parallel processing (Japanese Examined Patent Application Publication No. 2741793).
When the degree of similarity in terms of a local part of an object model is evaluated, if a part of an object is hidden, there is a possibility that difficulty occurs in the evaluation of the degree of similarity. A technique for avoiding such difficulty is disclosed in Japanese Patent Laid-Open No. 11-15495. In this technique, matching between a local part of an object and a local model is evaluated, and the likelihood of presence of the object is calculated for various local parts of the object. In accordance with the Dempster-Shafer technique or the fuzzy technique, the overall likelihood of presence of the image is then determined from the likelihood of presence calculated on the basis of individual local parts, thereby enhancing the reliability of recognition.
Japanese Patent Laid-Open No. 6-176158 discloses a technique in which the degree of similarity of feature vectors of an input pattern with respect to a category is calculated individually for each feature vector, and the overall degree of similarity is determined using the degrees of similarity of respective feature vectors normalized with respect to a maximum degree of similarity. Finally, recognition is performed on the basis of the overall degree of similarity.
Japanese Patent Laid-Open No. 9-153021 discloses a parallel processing apparatus in which an input digital signal is divided into a plurality of parts and the divided parts are processed in parallel by a plurality of processors, wherein division of the input digital signal into the plurality of parts is performed such that the calculation cost is minimized and the performance is optimized depending on the input digital signal.
However, in the technique disclosed in Japanese Patent Laid-Open No. 11-15945, when there are a plurality of categories in object models, it is not disclosed which local model should be employed and how matching results are consolidated. Furthermore, when the overall likelihood of presence of a feature is determined using non-additive measures on the basis of the Dempster-Shafer technique, it is not necessarily ensured that the resultant overall likelihood indicates optimum estimation.
Another problem is that when the size of an object in an image to be recognized is different from that of object model, or when an image includes a plurality of objects with different sizes, the technique encounters difficulty. Recognition may be possible if a plurality of object models corresponding to various sizes are prepared and if the degree of similarity is calculated one by one for all object models corresponding to different sizes. However, this needs a large-scale circuit (large memory size) and the processing efficiency is low.
In the parallel processing apparatus disclosed in Japanese Patent Laid-Open No. 9-153021, if input data includes a plurality of objects with different sizes, it is difficult to properly divide the input data. That is, when the type or size of an object is unknown, if an input signal is simply divided in a fixed manner, parallel processing for pattern recognition cannot be properly performed.
In the pattern recognition apparatus disclosed in Japanese Patent Laid-Open No. 6-176158, the improvement in the memory efficiency and the reduction in the circuit size cannot be achieved. In general, when pattern recognition is performed using a hierarchical parallel processing circuit (using a technique disclosed, for example, in Japanese Examined Patent Application Publication No. 2741793), detection of a plurality of features at sampling point positions on the input data is performed simultaneously and in parallel. Therefore, depending on the size of an input image, a large number of elements are required in a low-level layer, and thus a large-scale circuit is needed.